[HTML][HTML] Heat transport and nonlinear mixed convective nanomaterial slip flow of Walter-B fluid containing gyrotactic microorganisms

MI Khan, F Alzahrani, A Hobiny - Alexandria Engineering Journal, 2020 - Elsevier
Here nonlinear mixed convective nanoliquid slip flow of Walter-B fluid is addressed subject
to stretched surface with gyrotactic microorganisms. The flow is generated via nonlinear …

On the evaluation of thermal conductivity of nanofluids using advanced intelligent models

A Hemmati-Sarapardeh, A Varamesh, MN Amar… - … Communications in Heat …, 2020 - Elsevier
Accurate knowledge of thermal conductivity (TC) of nanofluids is emphasized in studies
related to the thermophysical aspects of nanofluids. In this work, a comprehensive review of …

nn-PINNs: Non-Newtonian physics-informed neural networks for complex fluid modeling

M Mahmoudabadbozchelou, GE Karniadakis, S Jamali - Soft Matter, 2022 - pubs.rsc.org
Time-and rate-dependent material functions in non-Newtonian fluids in response to different
deformation fields pose a challenge in integrating different constitutive models into …

CO₂ geological sequestration in heterogeneous binary media: Effects of geological and operational conditions

R Ershadnia, CD Wallace… - Advances in Geo-Energy …, 2020 - yandy-ager.com
Realistic representation of subsurface heterogeneity is essential to better understand and
effectively predict the migration and trapping patterns of carbon dioxide (CO2) during …

Predicting formation damage of oil fields due to mineral scaling during water-flooding operations: Gradient boosting decision tree and cascade-forward back …

A Larestani, SP Mousavi, F Hadavimoghaddam… - Journal of Petroleum …, 2022 - Elsevier
Water-flooding is one of the main options employed by the oil industry to meet the world's
ever-increasing demand for oil, as the primary source of energy. This approach is highly …

Modeling of methane adsorption capacity in shale gas formations using white-box supervised machine learning techniques

MN Amar, A Larestani, Q Lv, T Zhou… - Journal of Petroleum …, 2022 - Elsevier
Energy demand is increasing worldwide and shale gas formations have gained increasing
attention and have become crucial energy sources. Therefore, accurate determination of …

[HTML][HTML] Flow modeling of high-viscosity fluids in pipeline infrastructure of oil and gas enterprises

I Beloglazov, V Morenov, E Leusheva - Egyptian Journal of Petroleum, 2021 - Elsevier
Today, the issues related to solving the problem of finding an effective distribution of oil flows
through the system of oil pipelines in order to reduce the total energy consumption are …

Prediction of pressure in different two-phase flow conditions: machine learning applications

E Khamehchi, A Bemani - Measurement, 2021 - Elsevier
The accurate prediction of pressure has extensive applications in the petroleum industry,
especially in the optimization of continuous field production, quantifying reservoir …

Estimating the heat capacity of non-Newtonian ionanofluid systems using ANN, ANFIS, and SGB tree algorithms

R Daneshfar, A Bemani, M Hadipoor, M Sharifpur… - Applied Sciences, 2020 - mdpi.com
This work investigated the capability of multilayer perceptron artificial neural network (MLP–
ANN), stochastic gradient boosting (SGB) tree, radial basis function artificial neural network …

Modeling interfacial tension of methane-brine systems at high pressure and high salinity conditions

H Mehrjoo, M Riazi, MN Amar… - Journal of the Taiwan …, 2020 - Elsevier
Natural gas which consists mainly of methane (usually more than 90% in volume), is
becoming increasingly an important and efficient source of energy because of the lower …